Macnica Ventures

Total investments

2

Average round size

8M

Portfolio companies

2

Areas of investment
SoftwareArtificial IntelligenceHealth CareRoboticsCyber SecurityNetwork SecurityComputer

Summary

Besides, a startup requires to be at the age of 4-5 years to receive the investment from the fund. Among the most popular fund investment industries, there are Cyber Security, Software. Among the most popular portfolio startups of the fund, we may highlight Attivo Networks, Catalia Health. The fund has no exact preference in a number of founders of portfolio startups.

We also calculated 1 valuable employee in our database.

The typical case for the fund is to invest in rounds with 7 participants. Despite the Macnica Ventures, startups are often financed by Silicon Valley Growth Syndicate, MedTech Innovator, MIT Media Lab. The meaningful sponsors for the fund in investment in the same round are Secure Octane, Q Venture Partners, Omidyar Technology Ventures. In the next rounds fund is usually obtained by Singtel Innov8, ForgePoint Capital, Tony Ling.

Deals in the range of 5 - 10 millions dollars are the general things for fund. The fund is constantly included in less than 2 deals per year. The important activity for fund was in 2017.

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Investments analytics

Analytics

Total investments
2
Lead investments
0
Investments by industry
  • Robotics (1)
  • Health Care (1)
  • Artificial Intelligence (1)
  • Cyber Security (1)
  • Computer (1)
  • Show 2 more
Investments by region
  • United States (2)
Peak activity year
2017

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Quantitative data

Avg. startup age at the time of investment
10
Group Appearance index
1.00

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
Attivo Networks 10 May 2017 Software, Cyber Security, Network Security, Computer Early Stage Venture 15M United States, California, Fremont
How we get our data

At Unicorn Nest, we combine cutting-edge technology with human expertise to build one of the most reliable venture capital databases in the market. Our process begins with automated AI-enhanced data collection, leveraging the full potential of Large Language Models (LLMs).

Later, our team of analysts takes it further with manual verification, using proprietary tools for data cleaning and validation to ensure accuracy and reliability. We cross-check and enhance our findings through press and media monitoring, integrating information from trusted news outlets and venture capital aggregators. Finally, we stay ahead of the curve by monitoring social networks like LinkedIn and X.com.